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2 months ago

Data Scientist (Pricing & Packaging)

Work format
onsite
Work type
fulltime
Grade
senior
English
c1
Country
Sweden
This vacancy is from Hirify.Global listVacancy from Hirify Global, list of international tech companies
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Job description

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TL;DR
Data Scientist (SQL/Python/Economics): Developing pricing and packaging strategies by analyzing usage, cost, and willingness-to-pay data with an accent on unit economics and revenue modeling. Focus on designing pricing experiments and building systems to operationalize pricing decisions.

Company

Lovable is a talent-dense software creation platform that enables users to transform raw ideas into real products using AI.

What you will do

  • Own the analytics behind pricing and packaging, monitoring the impact of changes on revenue, conversion, and retention.
  • Build models for unit economics, willingness to pay, and price sensitivity to drive concrete pricing bets.
  • Design and execute pricing and packaging experiments and make decisive actions based on results.
  • Develop systems to operationalize pricing decisions, including personalized discounting models.
  • Collaborate with finance, product, and growth teams to sequence and implement pricing changes.

Requirements

  • Strong proficiency in SQL, Python, applied statistics, and experimentation.
  • Deep understanding of unit economics (LTV, margin, token/infrastructure costs, subscription/credit models).
  • Ability to handle causal questions where standard A/B tests are not possible.
  • Strategic judgment regarding the tradeoff between growth and monetization.
  • Entrepreneurial spirit and ability to thrive with high autonomy.
  • English: C1+ proficiency required as it is the company language.

Culture & Benefits

  • Work within a small, talent-dense team emphasizing extreme ownership and high velocity.
  • Low-ego collaboration environment focused on making a significant impact on the digital world.
  • Modern tech stack including BigQuery, GCP, and AI-integrated tools.

Hiring process

  • Introductory call with the recruiting team.
  • Interview with the hiring manager.
  • Take-home case study.
  • "Most Impressive Project" session and cross-functional interviews.
  • Final conversation with company leadership.

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